code: def test_actual_results_without_weights(params):
      """Test that the actual results are the expected ones."""
      arr_actual = MultivariateClassifier(**params).fit(X, y).predict(X)
      predictions = []
      if isinstance(params["estimator"], list):
          for i in range(n_features):
              predictions.append(
                  params["estimator"][i]
                  .fit(X[:, i], y)
                  .predict(X[:, i])
              )
      else:
          for i in range(n_features):
              predictions.append(
                  params["estimator"].fit(X[:, i], y).predict(X[:, i])
              )
      predictions = np.asarray(predictions)
      arr_desired = []
      for i in range(n_samples):
          arr_desired.append(np.argmax(np.bincount(predictions[:, i])))
      np.testing.assert_allclose(
          arr_actual, arr_desired, atol=1e-5, rtol=0.0
      )
  
file_path: pyts/pyts/multivariate/classification/tests/test_multivariate.py
imports: import numpy
  import pytest
  import re
  from pyts.classification import SAXVSM, BOSSVS
  from pyts.multivariate.classification import MultivariateClassifier
  from pyts.transformation import BOSS
label_desc: Use image node_id 3 for calling a global function with example usage: test_actual_results_without_weights(params) without return types